* Knowledge graphs are used in development to structure complex data relationships, drive intelligent search functionality, and build powerful AI applications that can reason over different data types.
• Knowledge graphs can connect data from both structured and unstructured sources (databases, documents, etc.), providing an intuitive and flexible way to model complex, real-world scenarios.
• Unlike tables or simple lists, knowledge graphs can capture the meaning and context behind the
data, allowing you to uncover insights and connections that would be difficult to find with conventional databases.
• This rich, structured context is ideal for improving the output of large language models (LLMs),
because you can build more relevant context for the model than with semantic search alone.